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Traffic Crash Evolution Characteristic Analysis and Spatiotemporal Hotspot Identification of Urban Road Intersections

Author

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  • Zeyang Cheng

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    School of Transportation, Southeast University, Nanjing 211189, China)

  • Zhenshan Zu

    (Traffic Police Brigade of Wujiang Public Security Bureau, Suzhou 215200, China)

  • Jian Lu

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    School of Transportation, Southeast University, Nanjing 211189, China)

Abstract

Road traffic safety is a key concern of transport management as it has severely restricted Chinese economic and social development. With the objective to prevent and reduce road traffic crashes, this study proposes a comprehensive spatiotemporal analysis method that integrates the time-space cube analysis, spatial autocorrelation analysis, and emerging hot spot analysis for exploring the traffic crash evolution characteristics and identifying crash hot spots. These analyses are all conducted by the corresponding toolbox of ArcGIS 10.5. Then, a small sized-city of China (i.e., Wujiang) is selected as the case study, and the historical traffic crash data occurring at the road intersections of Wujiang for the year 2016 are analyzed by the proposed method. The analysis process identifies the high incidence locations of traffic crashes, then presents the spatial change trend and statistical significance of the crash locations. Finally, different types of crash hotspots, as well as their evolution patterns over time, are determined. The results illustrate that the traffic crash hotspots of road intersections are primarily distributed in the Northeast area of Wujiang’s major urban area, while the crash cold spots are concentrated in the Southwest of Wujiang, which points out the direction for crash prevention. In addition, the finding has a potential engineering application value, and it is of great significance to the sustainable development of Wujiang.

Suggested Citation

  • Zeyang Cheng & Zhenshan Zu & Jian Lu, 2018. "Traffic Crash Evolution Characteristic Analysis and Spatiotemporal Hotspot Identification of Urban Road Intersections," Sustainability, MDPI, vol. 11(1), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2018:i:1:p:160-:d:193902
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    References listed on IDEAS

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    Cited by:

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    2. Fu, Xin & Xu, Chengyao & Liu, Yuteng & Chen, Chi-Hua & Hwang, F.J. & Wang, Jianwei, 2022. "Spatial heterogeneity and migration characteristics of traffic congestion—A quantitative identification method based on taxi trajectory data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
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